M. Mobasseri, M. Shirmohammadi, T. Amiri, N. Vahed, H. Hosseini Fard, M. Ghojazadeh, Prevalence and incidence of type 1 diabetes in the world: a systematic review and meta-analysis. Health Promot. Perspect. 10, 98–115 (2020). https://doi.org/10.34172/hpp.2020.18
Article PubMed PubMed Central Google Scholar
E.S. Strotmeyer, A.R. Steenkiste, T.P. Foley Jr., S.L. Berga, J.S. Dorman, Menstrual cycle differences between women with type 1 diabetes and women without diabetes. Diabetes Care 26, 1016–1021 (2003). https://doi.org/10.2337/diacare.26.4.1016
E. Codner, P.M. Merino, M. Tena-Sempere, Female reproduction and type 1 diabetes: from mechanisms to clinical findings. Hum. Reprod. Update 18, 568–585 (2012). https://doi.org/10.1093/humupd/dms024
Article CAS PubMed Google Scholar
E. Codner, H.F. Escobar-Morreale, Clinical review: Hyperandrogenism and polycystic ovary syndrome in women with type 1 diabetes mellitus. J. Clin. Endocrinol. Metab. 92, 1209–1216 (2007). https://doi.org/10.1210/jc.2006-2641
Article CAS PubMed Google Scholar
X. Gaete, M. Vivanco, F.C. Eyzaguirre, P. Lopez, H.K. Rhumie, N. Unanue, E. Codner, Menstrual cycle irregularities and their relationship with HbA1c and insulin dose in adolescents with type 1 diabetes mellitus. Fertil. Steril. 94, 1822–1826 (2010). https://doi.org/10.1016/j.fertnstert.2009.08.039
Article CAS PubMed Google Scholar
M.G. Tolpygina, M.A. Tarasova, N.V. Borovik, E.V. Misharina, A.V. Tiselko, The influence of compensation of carbohydrate metabolism on the restoration of ovulatory function in women of reproductive age with type 1 diabetes. J. Obst. Women’s Dis. 67, 42–49 (2018). https://doi.org/10.17816/JOWD67542-49
T. Battelino, N. Danne, R.M. Bergenstal et al. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care 42, 1593–1603 (2019). https://doi.org/10.2337/dci19-0028
Article PubMed PubMed Central Google Scholar
C.R. Marling, N.W. Struble, R.C. Bunescu, J.H. Shubrook, F.L. Schwartz, A consensus perceived glycemic variability metric. J. Diabetes Sci. Technol. 7, 871–879 (2013). https://doi.org/10.1177/193229681300700409
Article PubMed PubMed Central Google Scholar
R.W. Beck, T. Riddlesworth, K. Ruedy et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: The DIAMOND Randomized Clinical Trial. JAMA 317, 371–378 (2017). https://doi.org/10.1001/jama.2016.19975
Article CAS PubMed Google Scholar
K.D. Kohnert, P. Heinke, G. Fritzsche, L. Vogt, P. Augstein, E. Salzsieder, Evaluation of the mean absolute glucose change as a measure of glycemic variability using continuous glucose monitoring data. Diabetes Technol. Ther. 15, 448–454 (2013). https://doi.org/10.1089/dia.2012.0303
Article CAS PubMed Google Scholar
J. Bolinder, R. Antuna, P. Geelhoed-Duijvestijn, J. Kröger, R. Weitgasser, Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet 388, 2254–2263 (2016). https://doi.org/10.1016/S0140-6736(16)31535-5
I.B. Hirsch, Glycemic variability and diabetes complications: does it matter? Of course it does! Diabetes Care 38, 1610–1614 (2015). https://doi.org/10.2337/dc14-2898
Article CAS PubMed Google Scholar
A.M. Gomez, D.C. Henao, A. Imitola Madero et al. Defining high glycemic variability in type 1 diabetes: comparison of multiple indexes to identify patients at risk of hypoglycemia. Diabetes Technol. Ther. 21, 430–439 (2019). https://doi.org/10.1089/dia.2019.0075
Article CAS PubMed Google Scholar
A.L. McCall, B.P. Kovatchev, The median is not the only message: a clinician’s perspective on mathematical analysis of glycemic variability and modeling in diabetes mellitus. J. Diabetes Sci. Technol. 3, 3–11 (2009). https://doi.org/10.1177/193229680900300102
Article PubMed PubMed Central Google Scholar
A.V. Tiselko, Risk factors for the development of pathological glucose variability in pregnant women with type 1 diabetes mellitus. J. Obstet. Womens Dis 68, 41–50 (2019). https://doi.org/10.17816/JOWD68341-50
A. Ceriello, A. Novials, E. Ortega, S. Canivell, L. La Sala, G. Pujadas, K. Esposito, D. Giugliano, S. Genovese, Glucagon-like peptide 1 reduces endothelial dysfunction, inflammation, and oxidative stress induced by both hyperglycemia and hypoglycemia in type 1 diabetes. Diabetes Care 36, 2346–2350 (2013). https://doi.org/10.2337/dc12-2469
Article CAS PubMed PubMed Central Google Scholar
K.G. Maier, X. Han, B. Sadowitz, K.L. Gentile, F.A. Middleton, V. Gahtan, Thrombospondin-1: a proatherosclerotic protein augmented by hyperglycemia. J. Vasc. Surg. 51, 1238–1247 (2010). https://doi.org/10.1016/j.jvs.2009.11.073
J.L. Kim, E.F. La Gamma, T. Estabrook, N. Kudrick, B.B. Nankova, Whole genome expression profiling associates activation of unfolded protein response with impaired production and release of epinephrine after recurrent hypoglycemia. PLoS One 12, e0172789 (2017). https://doi.org/10.1371/journal.pone.0172789
Article CAS PubMed PubMed Central Google Scholar
Y. Mao, K.X.Q. Tan, A. Seng, P. Wong, S.A. Toh, A.R. Cook, Stratification of patients with diabetes using continuous glucose monitoring profiles and machine learning. Health Data Sci. 2022, 9892340 (2022). https://doi.org/10.34133/2022/9892340
Article PubMed PubMed Central Google Scholar
T. Valente, A.K. Arbex, Glycemic variability, oxidative stress, and impact on complications related to type 2 diabetes mellitus. Curr. Diabetes Rev. 17(7), e071620183816 (2021). https://doi.org/10.2174/1573399816666200716201550
Article CAS PubMed Google Scholar
M.A. Darenskaya, L.I. Kolesnikova, S.I. Kolesnikov, Oxidative stress: pathogenetic role in diabetes mellitus and its complications and therapeutic approaches to correction. Bull. Exp. Biol. Med. 171(2), 179–189 (2021). https://doi.org/10.1007/s10517-021-05191-7
Article CAS PubMed PubMed Central Google Scholar
K. Stadler, Oxidative stress in diabetes. Adv. Exp. Med. Biol. 771, 272–287 (2012). https://doi.org/10.1007/978-1-4614-5441-0_21
Article CAS PubMed Google Scholar
S.J. Hamilton, G.F. Watts, Endothelial dysfunction in diabetes: pathogenesis, significance, and treatment. Rev. Diabet Stud. 10, 133–156 (2013).
Article PubMed PubMed Central Google Scholar
M. Grabia, K. Socha, J. Soroczyńska, A. Bossowski, R. Markiewicz-Żukowska, Determinants related to oxidative stress parameters in pediatric patients with type 1 diabetes mellitus. Nutrients 15, 2084 (2023). https://doi.org/10.3390/nu15092084
Article CAS PubMed PubMed Central Google Scholar
R.V. Kapustin, O.N. Arzhanova, A.V. Tiselko, Oxidative stress in pregnant women with diabetes mellitus. Diabetes 20, 461–471 (2017). https://doi.org/10.14341/DM8669
U. Asmat, K. Abad, K. Ismail, Diabetes mellitus and oxidative stress-A concise review. Saudi Pharm. J. 24(5), 547–553 (2016). https://doi.org/10.1016/j.jsps.2015.03.013
S. Dinić, J. Arambašić Jovanović, A. Uskoković, M. Mihailović, N. Grdović, A. Tolić, J. Rajić, M. Đorđević, M. Vidaković, Oxidative stress-mediated beta cell death and dysfunction as a target for diabetes management. Front Endocrinol. 13, 1006376 (2022). https://doi.org/10.3389/fendo.2022.1006376
C. Tatone, F. Amicarelli, The aging ovary-the poor granulosa cells. Fertil. Steril. 99, 12–17 (2013). https://doi.org/10.1016/j.fertnstert.2012.11.029
Article CAS PubMed Google Scholar
N.A. ElSayed, G. Aleppo, V.R. Aroda, et al., on behalf of the American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Care in Diabetes-2023. Diabetes Care 46, S19–S40 (2023). https://doi.org/10.2337/dc23-S002.
T. Danne, R. Nimri, T. Battelino et al. International consensus on use of continuous glucose monitoring. Diabetes Care 40, 1631–1640 (2017). https://doi.org/10.2337/dc17-1600
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